"There is a stigma against market timing. This stigma existed for good reasons, but the explosion of vast data sets and new analytical techniques has now made timing the market possible. Just as it was considered irresponsible to time the market over the last 30 years, it will be considered irresponsible NOT to time the market in the next 30 years." Light food and drinks provided. The speakers will be Blair Hull, most recently founder of Ketchum Trading, and Matthew Dixon of the Illinois Institute of Technology's Stuart School of Business and founder of Quiota, LLC.

In this Q&A Ari explains why the use of machine learning for automation is unlikely to overtake most organizational roles in the near future, why data is so incredibly important, the continucontinuous need for data scientists and his priorities for 2016.

Google DeepMind claims to have significantly improved computer-generated speech with its AI technology, paving the way forward for sophisticated talking machines like those seen in sci-fi films like "Her" and "Ex-Machina." The London-based research lab, acquired by Google in 2014 for a reported 400 million, announced on Thursday that it has developed a talking computer programme called "WaveNet" that halves the quality gap that currently exists between human speech and computer speech. Although WaveNet sounds more like a human voice than existing artificial voice generators -- known as "text-to-speech" (TTS) systems -- it requires too much computing power to make it practical, meaning Google won't be integrating it into its products any time soon, according to The Financial Times. Aäron van den Oord, a research scientist, at DeepMind said: "Mimicking realistic speech has always been a major challenge, with state-of-the-art systems, composed of a complicated and long pipeline of modules, still lagging behind real human speech. Our research shows that not only can neural networks learn how to generate speech, but they can already close the gap with human performance by over 50%.

I'm also the CEO of a company that is utilizing A.I. technologies to improve K-12 education through synchronized planning calendars. During my journey with EduSync, I've learned a few things about what artificial intelligence is, what it isn't, and how it can have a positive impact in K-12. Artificial intelligence is young--newborn young. In simple terms, it is the attempt to build a computer that operates like a human brain. This involves programming software that learns from experience (machine learning or ML), understands human language including common usage and context (natural language processing or NLP), and has the ability to figure out what to do in the future based on the past (predictive analytics).

As the health care industry shifts from fee-for-service to value-based care, the ability to deploy effective population health initiatives has emerged as a critical factor for the success of organizations. With more risk shifting to providers, organizations need to go beyond merely analyzing data to stratify patients into condition-specific cohorts; they need to develop sophisticated approaches for weighing a wide range of variables to selectively deliver interventions and guidance to caregivers that help improve outcomes while lowering costs. Population health has the promise to deliver big results, but many providers are facing roadblocks along the way. In order to successfully engage in population health, providers should focus on five critical areas. Successful population health initiatives need access to relevant, accurate data.

We live in a society where human health is increasingly enhanced by artificial augmentation and implantation including hip replacements and hearing aids. French company Carmat have been working for 15 years on the artificial heart, a device that completely replaces the human heart in people with end stage heart disease and a life expectancy of less than two weeks without the surgery. They've recently announced their second trial, commencing in 2017 with the aim to achieve European approval for their device. The Carmat device differs to other robotic heart devices as it is meant to be used in cases of terminal heart failure, instead of being used as a bridge device while the patient awaits a transplant. In Carmat's design, two chambers are each divided by a membrane that holds hydraulic fluid on one side.

Over the past century, we have made massive strides in the rights revolution. These include rights for women, children, the LGBT community, animals, and so much more. Exploring the future, we must ask ourselves: what next? Will we ever fight for the rights of artificial intelligence? If so, when will this AI rights revolution occur, and what will it look like?

A Deutsche Telekom official says artificial intelligence (AI) will be needed to break smart city data out of its silos. As reported by Mobile World Live, thoughts about smart city evolution appeared on the blog of Claudia Nemat, the Deutsche Telekom (DT) board member who oversees Technology & Innovation Europe. In her piece, Nemat described current smart city practices as trapping data from sensors in an isolated "landlocked lake." But as sensors proliferate at blinding speed in global smart cities, the rivers of data being produced will turn into oceans. This will be complicated by the multiple digital platforms running simultaneously in each city.

To gain intuition and reasoning of a model is to have understanding and trust--transparency. When you strike a nail with a hammer, it's pretty predictable what might happen: the nail could get hit, the hammer could miss, or very rarely, the hammer's head may fly off of the handle. When you replace the hammer with a black box that works correctly 99.999% of the time, but for 0.001%, something completely unpredictable happens, then there's a problem with volatility because that unpredictable event may have unacceptable consequences. I think explainable AI could help with intuitive and more fine-grained risk analysis, and that's certainly a good thing in high-stakes applications such as defense.

Generating speech from a piece of text is a common and important task undertaken by computers, but it's pretty rare that the result could be mistaken for ordinary speech. A new technique from researchers at Alphabet's DeepMind takes a completely different approach, producing speech and even music that sounds eerily like the real thing. Early systems used a large library of the parts of speech (phonemes and morphemes) and a large ruleset that described all the ways letters combined to produce those sounds. The pieces were joined, or concatenated, creating functional speech synthesis that can handle most words, albeit with unconvincing cadence and tone. WaveNet, as the system is called, takes things deeper.